MetaboMSDIA: A tool for implementing data-independent acquisition in metabolomic-based mass spectrometry analysis

Data-dependent acquisition (DDA) is the most widely used mode in untargeted metabolomic analysis despite its limited tandem mass spectrometry (MS2) detection coverage. We present MetaboMSDIA for complete processing of data-independent acquisition (DIA) files by the extraction of multiplexed MS2 spectra and further identifi-cation of metabolites in open libraries. In the analysis of polar extracts from lemon and olive fruits, DIA allows one to obtain multiplexed MS2 spectra for 100% of precursor ions compared to 64% of precursor ions from average MS2 acquisition in DDA. MetaboMSDIA is compatible with MS2 repositories and homemade libraries prepared by analysis of standards. An additional option is based on filtering molecular entities by searching for selective fragmentation patterns according to selective neutral losses or product ions to target the annotation of families of metabolites. Combining both options, the applicability of MetaboMSDIA was tested by annotating 50 and 35 metabolites in polar extracts from lemon and olive fruit, respectively. MetaboMSDIA is particularly proposed to increase the acquisition coverage in untargeted metabolomics and to improve spectral quality, which are two critical pillars for the tentative annotation of metabolites. The R script used in MetaboMSDIA workflow is available at github repository (https://github.com/MonicaCalSan/MetaboMSDIA).

Automated summary

MetaboMSDIA is a complete processing method for data-independent acquisition (DIA) files that extracts multiplexed MS2 spectra and identifies metabolites from open libraries. It improves the acquisition coverage and spectral quality in untargeted metabolomics, which are crucial for the tentative annotation of metabolites.